Nature Physics

In living systems across developmental and cancer biology, populations of cells on surfaces organize themselves into aggregates that mediate function and disease. Recent experimental studies have identified that such aggregates can have emergent fluid-like properties such as surface tension, yet the physical origin of these properties is not clear. Here, we develop a minimal cell-based model in which cell-cell and cell-substrate interactions are governed by active intermittent attachments. We explain the transition of cells from a dilute population to a dense aggregate, and quantify the emergent material properties underpinning this transition. We use our model to interpret experiments on dewetting of aggregates of MDA-MDB-231 cancer cells and shape fluctuations of surface-associated OVCAR3 cell aggregates. Finally, we show how spatial heterogeneity in attachments governs collective chemotaxis of cell aggregates. Together, these results reveal how active intermittent attachments generate cell aggregates with emergent material properties, with broad implications for development and cancer.

A central problem in soft and biological physics is how molecular-scale activity and remodelling coarse-grain into emergent mechanical laws at larger scales. In growing cell walls (polymeric composite materials that surround 90% of living organisms cells) irreversible deformation is not controlled by elastic stress alone. Instead, growth depends on the interplay between energy storage, dissipation, and the local timing of viscoelastic relaxation. Although dynamic atomic force microscopy (AFM) resolves storage and loss moduli (E', E'') of living walls at nanometre resolution, these observables have remained phenomenological and disconnected from constitutive field variables. Here we introduce a physics-based inversion framework that converts AFM measurements of epidermal cells of living Arabidopsis plants into spatially resolved fields of stiffness k, viscosity , and relaxation time{tau} . By analysing the spatial gradients of E' and E'', we uncover organized mechanical heterogeneities governed by cellular confinement and stress focusing. We demonstrate that the local relaxation time is encoded directly in the coupling between storage and dissipation, yielding the pointwise relation{tau} = (1/{omega}) {partial}E/{partial}E, where{omega} is the indentation frequency. This relation enables model-independent extraction of mechanical timescales and establishes a general route from nanoscale non-equilibrium rheology to continuum descriptions of growth in living and active soft materials. SignificanceHow molecular-scale activity gives rise to tissue-scale form is a central challenge in biological physics. Although growth is fundamentally a non-equilibrium mechanical process, experimental measurements at the nanoscale have not been directly connected to the constitutive parameters that govern morphogenesis. We introduce a framework that converts dynamic atomic force microscopy maps of storage and loss moduli into spatially resolved fields of stiffness, viscosity, and relaxation time in living cell walls. By revealing that mechanical relaxation is encoded in the local coupling between elastic storage and viscous dissipation, our work provides a route from nanoscale rheology to growth-relevant mechanical timing. This establishes a quantitative bridge between molecular remodeling and continuum mechanics, enabling direct experimental constraints on multiscale theories of morphogenesis.

Directed cell migration underlies many biological phenomena, from embryonic development to tumor metastasis and organ fibrosis. Most cells typically migrate toward stiffer regions of their extracellular matrix -a behavior known as positive durotaxis. Here we show that culture on rigid plastic reinforces this response, whereas preconditioning in soft 3D physiomimetic environments reprograms migration towards softer environments, a phenomenon known as negative durotaxis. Fetal rat lung fibroblasts preconditioned in 3D physiomimetic hydrogels exhibited negative durotaxis and accumulated near [~]5 kPa, corresponding to the physiological stiffness of the lung. In contrast, genetically identical cells maintained on conventional 2D plastic substrates migrated up stiffness gradients, toward stiffer regions. Although both populations displayed a biphasic force-stiffness relationship, they differed in force magnitude and cytoskeletal organization. Molecular-clutch modeling revealed that durotaxis reversal emerges from two distinct mechanical regimes: a mechanosensitive, high-motor-clutch state that stabilizes adhesions on stiff substrates and drives positive durotaxis, and a low-motor, weak-adhesion state in which clutch slippage on the stiff side causes negative durotaxis. Our results show that durotaxis direction is not an intrinsic cellular property. Rather, it emerges from the interplay between motor activity and adhesion dynamics and can be tuned by culture conditions.

Glassy dynamics in active biological cells remain a subject of debate, as cellular activity rarely slows enough for true glassy features to emerge. In this study, we address this paradox of glassy dynamics in epithelial cells by integrating experimental observations with an active vertex model. We demonstrate that while crowding is essential, it is not sufficient for glassy dynamics to emerge. A mechanochemical feedback loop (MCFL), mediated by cell shape changes through the contractile actomyosin network, is required to drive glass transition in dense epithelial tissues, as revealed via a crosstalk between actin-based cell clustering and dynamic heterogeneity in experiments. Incorporating MCFL into the vertex model reveals contrasting results from those previously predicted by theories- we show that the MCFL can counteract cell division-induced fluidisation and enable glassy dynamics to emerge through active cell-to-cell communication. Furthermore, our analysis reveals, for the first time, the existence of novel collective mechanochemical oscillations that arise from the crosstalk of two MCFLs. Together, we demonstrate that an interplay between crowding and active mechanochemical feedback enables the emergence of glass-like traits and collective biochemical oscillations in epithelial tissues with active cell-cell contacts.

Cells sense and respond to the mechanical properties of their environment, yet the minimal physical principles sufficient to reproduce mechanotransduction and durotaxis remain debated. This work introduces FraCeMM, a physics-first mechanochemical simulation framework coupling stochastic ligand-integrin-talin binding to a deformable soft-body cell model on an elastic substrate. Without imposed polarity, directional cues, or migration rules, the model reproduces hallmark mechanobiological behaviors including stiffness-dependent spreading, traction reinforcement, focal adhesion asymmetry, and directed durotaxis. A finite pool of adhesion molecules, mechanically coupled through elastic linkages, drives emergent force asymmetry and polarization via self-consistent feedback between stochastic binding, molecular availability, and substrate stiffness. Despite minimal assumptions and a coarse-grained molecular representation, resulting traction forces, adhesion loads, and migration speeds fall within experimentally reported ranges. These results support the view that local force balance, limited adhesion resources, and mechanically binding are sufficient to generate adaptive mechanosensing and directed migration, establishing a transparent and extensible foundation for computational mechanobiology.

Robust development depends on maintaining correct proportions as overall size varies. What controls and limits this ability to scale remains poorly understood in part due to the complex interplay between mechanical and biochemical factors within developing embryos. Using confinement of dissociated embryonic presomitic mesoderm cells, combined with imaging and chemical perturbations, we identified aggregation as the initial event in de novo anterior-posterior axis patterning. Using a continuum model solely based on cell-cell attraction, we quantitatively map out how the time available for aggregation-driven patterning limits the system size over which scaling can be maintained: Small systems allow for rapid and robust pattern scaling whereas coarsening dynamics substantially de-lay the appearance of a scaled pattern in large systems. Our experiments quantitatively confirm these predicted scaling regimes. Together, our results suggest a developmental time-size tradeoff on the scaling of aggregation-driven patterns.

Receptor-mediated ligand endocytosis is traditionally viewed as a negative feedback mechanism for signal attenuation. Here we show that ligand removal can paradoxically enhance directional information in autonomous cell-cell attraction. Many cell systems migrate toward one another in the absence of externally imposed gradients, implying that secretion, diffusion, and uptake must themselves generate usable directional cues. We develop a surface-resolved theory of a finite-sized detector exposed to a nearby source and derive analytical expressions for the steady-state ligand field. The resulting concentration profiles are governed by a single dimensionless Damkohler number that compares receptor-mediated endocytosis to diffusive ligand transport. Increasing ligand removal lowers extracellular ligand concentrations and reduces absolute concentration differences across the detector surface, but preferentially enhances relative surface anisotropy. Thus, destroying the signal can increase the usable information encoded in relative gradients. Incorporating nonlinear downstream processing reveals a tradeoff between contrast enhancement and signal depletion that yields a well-defined optimal endocytosis rate, in a regime consistent with experimentally measured receptor internalization kinetics. These results recast receptor-mediated endocytosis as an extracellular information-processing mechanism that reshapes self-generated gradients to enhance directional information.

The mechanical toughness of bone and teeth relies on residual stresses generated during mineralisation, where the dehydration of collagen fibrils leads to contraction, putting the mineral phase under compression. While macroscopic stiffening of collagen upon drying is well-documented, the atomic-level structural rearrangements driving this phenomenon have remained elusive. By performing molecular dynamics simulations, we demonstrate that collagen contraction is not homogeneous but is driven by specific charged motifs. We identify a critical sequence-dependent rule for contraction: oppositely charged side chains must be separated by at least four residues to drive backbone contraction. While salt bridges can form between side chains at a distance less than four residues without perturbing the helix, those at greater distances cannot form without rupturing backbone hydrogen bonds. Consequently, dehydration forces these distant charges together, breaking local backbone structure and driving collagen contraction. These findings imply that collagen sequences are evolutionarily tuned to actively control tissue mechanics and redefines collagen as an active mechanical element rather than a passive scaffold. Furthermore, this framework provides a molecular basis for understanding mechanical failure associated with pathologies and ageing, while simultaneously opening avenues for designing bio-inspired materials with tunable pre-stress and fracture resistance.

Cells navigate complex tissue microenvironments defined by intricate physical cues, yet how they interpret the three-dimensional geometry of the extracellular matrix (ECM) remains an open question. Current models often fail to account for the tortuous architectures found in physiological tissues. Here, we demonstrate that ECM curvature functions as a tissue-specific geometric code read by the cell nucleus. By mapping collagen architectures across cancers and tissues, we find unique curvature fingerprints preserved during metastasis. Using micro-engineered substrates, we show that high curvature imposes localized nuclear bending stress, triggering a Lamin A/C-cPLA2-Ca2+ mechanotransductive cascade. This sensor rewires the cytoskeleton from longitudinal stress fibers to a cortical actomyosin network, driving a sharp transition from fast mesenchymal migration to a slower, exploratory amoeboid phenotype. We term this "nuclear curvotaxis", establishing a physical principle linking static geometry to dynamic strategy, with implications for predicting metastatic risk, understanding immune exclusion, and designing bio-instructive scaffolds for tissue engineering.

The development, maintenance and repair of epithelial tissues critically rely on adhesion complexes that ensure structural integrity while enabling dynamic remodeling. Such tissue remodeling underpins both physiological morphogenesis and pathological transformation. Central to these processes are mechanical forces, which tightly couple cytoskeletal organization to adhesion dynamics. Despite extensive investigations in two-dimensional (2D) systems, how these interactions are orchestrated within polarized three-dimensional (3D) epithelia remains largely unresolved. Here, we introduce a new, non-invasive strategy to probe localized force generation within 3D epithelial tissues. We engineered elastic polyacrylamide (PAAm) microbeads with cell-mimetic size and mechanical properties, enabling their seamless integration. In contrast to conventional bead injection approaches, these PAAm microbeads were spontaneously engulfed by the tissue, thereby establishing an intrinsic interface through which bead deformation can be directly correlated with local cytoskeletal architecture and adhesion organization, as visualized through high-resolution imaging combined with quantitative 3D computational reconstruction. Using this approach, we demonstrated that localized mechanical perturbations trigger pronounced cytoskeletal remodelling while preserving global tissue polarity. We further identified the extracellular matrix composition as key determinant of bead-tissue interactions, with collagen-I coating promoting robust adhesion and efficient incorporation. At the bead-cell interface, cells assembled tension-bearing focal adhesions and organized actin stress fibers, revealing the emergence of active cortical stress. Strikingly, quantitative analysis of bead deformation revealed a previously unrecognized mechanical duality: spatially segregated regions of pulling and pushing forces coexisted at the microscale, directly correlated with local cytoskeleton dynamics. This finding challenges the prevailing view of homogenous force application and instead supports a model in which cells deploy highly coordinated and spatially patterned force-generating strategies. Altogether, this integrative and non-invasive strategy offers a comprehensive pipeline for dissecting the dynamic interplay between cellular processes and tissue mechanics during morphogenesis in 3D model systems.

Plant cell growth depends on slow, irreversible creep of the fibrous cell wall stretched by turgor, yet the mechanics of creep--and how it differs from elasto-plastic deformation--remains uncertain1-3. Using multiscale modeling, we show how wall creep emerges from elementary sliding of cellulose microfibrils along their contact interfaces. A dominant sliding mode involves localized dislocation-like defects that stochastically nucleate at laterally bonded microfibril contacts and then glide along the interface by surmounting discrete energy barriers. Embedding these sliding events into Monte Carlo simulations of stretched cellulose networks recapitulates whole-wall creep kinetics. Elevated stress lowers sliding energy barriers and triggers rapid irreversible deformation characteristic of plastic flow. Compared with elasto-plastic stretching, creep induces less microfibril reorientation but promotes bundling, thereby reducing subsequent yielding. These results clarify the microfibril rearrangements underlying cell wall creep and show how they redistribute stress to permit sustained wall expansion at steady turgor without compromising structural integrity.

Understanding why specific metabolic states become stable in cancer has remained a fundamental challenge, as current pathway-centric frameworks lack a unifying physical principle governing global metabolic organization. We introduce the Metabolic Spin-Glass (MSG) model, which recasts cellular metabolism as a frustrated many-body system governed by a Hamiltonian that integrates reaction free energies, cofactor-mediated thermodynamic couplings, and patient-specific transcriptomic fields. The Hamiltonian is formulated as a binary optimization problem and solved using hybrid quantum annealing. Embedding gastric cancer transcriptomes (n=497) reveals that malignant phenotypes correspond to thermodynamically distinct ground states rather than isolated pathway perturbations. The Warburg effect emerges intrinsically as a thermodynamic phase transition, and stem-like tumors occupy the deepest attractor basin reflecting high energetic stability. A thermodynamic order parameter stratifies patients into prognostically distinct subtypes independently of transcriptomic classification, suggesting clinically applicable non-redundant biomarkers. This work establishes a spin-glass energy landscape framework for physically principled, patient-specific cancer metabolic stratification.

Collective cell migration is a critical process in embryogenesis and cancer invasion. Recent work has shown that uniform tissues can undergo sharp rheological transitions, with collective motion emerging above a critical cell motility. In vivo, however, migration typically involves multiple populations with distinct motile and adhesive properties, and how this heterogeneity shapes collective dynamics remains unclear. Here, using two different vertex model implementations, we show that migration of heterogeneous clusters through tissues is maximized at intermediate adhesion strength: too little and the cluster fragments, too much and cluster cell cohesion suppresses the rearrangements needed for forward motion. We test our model against recent and new data on zebrafish mesendoderm invasion, where graded Nodal signalling regulates both motility and adhesion differences. By mapping measured Nodal levels to mechanical parameters, the model not only reproduces migration outcomes across homogeneous and heterogeneous clusters, but also discriminates between alternative adhesion rules. Strikingly, the inferred parameters place the system near the predicted optimum, where adhesion is strong enough to maintain cohesion yet graded enough to allow selective coupling among heterogeneous neighbors. These results identify an optimal balance between cohesion and interfacial remodeling as a general principle coordinating collective invasion in heterogeneous tissues. Significance statementCells often migrate collectively during embryonic development and cancer invasion, but tissues are rarely uniform and different cells differ both in their adhesion and activity. Using models of tissue mechanics, we show that collective invasion is maximized at an intermediate level of adhesion within the migrating cluster cells: too little and the cluster falls apart, too much and it cannot advance. We test this principle against experiments in zebrafish gastrulation, where a signaling gradient simultaneously controls both cell motility and adhesion. The model reproduces migration outcomes across a range of experiments and identifies the adhesion rule cells use to selectively stick to neighbors. These results reveal a simple mechanical logic for how heterogeneous cell collectives coordinate invasion.

Cancer displays remarkable robustness, exemplified by its ability to develop resistance to virtually every therapy. Resistance has traditionally been explained by clonal selection of pre-existing mutations, but there is now abundant evidence for resistance by non-genetic pathways including signals from normal stromal and immune cells. It is largely unclear why normal cells help cancer cells overcome treatment. We propose that physiological circuits responsible for tissue homeostasis can explain why cells cooperate to produce pathological resistance to therapy. To show this, we construct mathematical models of physiological dynamics. We then simulate cancer treatments within the context of a functioning tissue. We find that classic examples of resistance to therapy can be explained by homeostatic feedback regulation - including BRAF inhibitors in melanoma and anti-angiogenic therapy. The homeostatic theory of resistance (HTOR) reframes resistance as a byproduct of tissue robustness, rather than solely tumor-specific adaptation. Finally, we analyze two large-scale single-cell RNAseq databases of normal and cancer samples: the Tabula Sapiens1 and the Curated Cancer Atlas2. We show that in multiple cancers (breast, colon, kidney, liver, lung, ovary, prostate, and skin), malignant cells preserve their tissue-specific homeostatic cell-signaling. We thus expect the robust feedback loops from healthy tissues to play a role in cancer.

Multiplexed tissue imaging (MTI) has revealed recurrent tumor microenvironment (TME) architectures with prognostic value, yet these measurements are inherently static, obscuring dynamic changes in the TME that govern therapeutic response. Here, we introduce a trajectory-centric framework that reconstructs continuous TME dynamics by integrating agent-based mathematical modeling and simulation with state space analysis. This approach yields a mechanistically constrained reference landscape built entirely from in silico simulation, and onto which static patient biospecimens can be projected and mapped onto simulated TME trajectories. Systematic simulation of tumor-immune interactions in triple-negative breast cancer identifies six metastable TME states connected by transition pathways spanning immune control to immune escape. Mapping MTI data from two independent patient cohorts, including longitudinal samples from a randomized immunotherapy trial, validates this landscape by positioning individual biospecimens along inferred TME trajectories rather than in static states. We show that treatment-phase TME states, but not pre-treatment configurations, robustly predict immunotherapy response, and identical terminal states can arise from distinct trajectory histories corresponding to immune failure or resolved inflammation. Thus, this framework enables mechanistic simulations to define a reference dynamical landscape that serves as a coordinate system for interpreting static clinical spatial data, providing a principled basis for evaluating consistency, predictiveness, and clinical relevance across independent patient cohorts. Altogether, this study advances spatial tumor profiling from static state classification of human tissues to dynamic trajectory inference, establishing a quantitative framework for trajectory-informed, state-guided, and temporally adaptive immunotherapy strategies.

While the regulation of bacterial cell size is widely studied across generations, the stochastic nature of cell volume growth remains elusive within a cell cycle. Here, we investigate the fluctuations of cell volume growth and report a deviation from standard white-noise models: the random growth rate exhibits subdiffusive dynamics. Specifically, the mean square displacement of the growth-rate noise scales as {Delta}t with an anomalous exponent {approx} 0.27. This low exponent implies strong negative temporal correlations in growth rate noise on timescales of minutes, which are significantly faster than those of gene expression dynamics. We attribute this phenomenon to the physical mechanics of the cell wall. By modeling the peptidoglycan network as a complex viscoelastic material with power-law-distributed relaxation times, we successfully recapitulate the observed subdiffusive behavior. Our results suggest that the heterogeneous mechanical constraints of the peptidoglycan network, rather than biological regulatory programs,govern the short-timescale fluctuations of bacterial growth.

Focal adhesions (FAs) are dynamic hubs for mechanotransduction, linking the extracellular matrix to actin fibers, intermediate filaments, and microtubules. Using cryo-electron tomography combined with 3-dimensional segmentation and subtomogram averaging, we visualize in situ the structural architecture of the FA environment at the leading edge of human fibroblasts. Our analysis reveals a rich architectural diversity within the FA landscape, where the spatial organisation and interplay of FA protein clusters, actin, vimentin, and microtubules change from the actin bundle core to its tip and across adjacent regions. Notably, we reveal diverse arrangements and connections of vimentin filaments, supporting their multifaceted role in the control and mechanics of adhesions. Together, these findings establish a structural framework for FA maturation and cytoskeletal integration, extending classical lamellipodial adhesion models and providing mechanistic insight into how FAs coordinate force transmission during cell migration.

Planarian fragments can regenerate with normal gross anatomy after a transient bioelectric perturbation yet display altered outcomes upon re-cutting, implying that regeneration can store a persistent hidden state. Here we formulate an open-path version of Tangential Action Spaces (TAS) for this setting. Regeneration after a given cut is represented as a prescribed coarse anatomical trajectory together with multiple physiological lifts in a higher-dimensional state space. A metric on physiological state space defines a baseline lift, an effective excess-cost functional, and a baseline-relative endpoint displacement that serves as written hidden regenerative state. Re-cutting converts this open-path construction into a challenge readout. Locally, the theory yields a cut-dependent memory co-metric that identifies latent directions that are easy, difficult, or inaccessible to rewrite. We show that this geometry is consistent with published observations of cryptic phenotypes, stable re-challenge ratios, and near-absorbing double-headed outcomes. A reduced rank-one latent-threshold realization fitted to published 8-OH immediate and re-challenge counts identifies a challenge-sensitive cryptic interval below the immediate double-headed threshold and predicts out-of-sample re-challenge penetrances near 15% for nigericin- and monensin-treated immediate single-headed survivors using only their immediate phenotype penetrances. As a mechanistic bridge, a local electrodiffusive in-silico example instantiates a local version of the physiological-state effort metric G. This metric defines the baseline lift and excess rewriting cost, in relative biophysical units, and yields explicit example local write geometry. An illustrative semimechanistic readout based on integrated wound-edge gap-junction contrast and Na/K-ATPase load reproduces the treated-family ordering and similar transfer predictions when the untreated baseline is softly anchored near zero. These quantitative layers are intended as proof-of-concept calibratability and mechanistic-grounding checks rather than full validation of the complete open-path model. The framework therefore turns cryptic regenerative memory into a geometric, costed, and experimentally testable object, yielding predictions about temporal-profile dependence, compensatory cancellation, sign-reversing controls, cut dependence, anisotropic rewriting, and multi-round accumulation of hidden regenerative state.

Adenosine 5-triphosphate (ATP) is found to form biomolecular condensates with proteins. However, without complementary proteins, the small size and high charge density of ATP molecules create substantial electrostatic and entropic barriers that prevent them from forming condensates. Here, we find that macromolecular crowding overcomes these energetic barriers, promoting ATP molecules to self-associate and form protein-free liquid-like condensates through screened electrostatic repulsion and enhanced hydrogen bonding. Importantly, ATP condensates are responsive to multiple stimuli and create distinct microenvironments that selectively enrich various guest molecules and protect ribonucleic acids from DNAzyme cleavage. These findings uncover important roles of ATP in forming dynamic, chemically distinct condensates via homotypic interactions, potentially expanding its classical view beyond a canonical energy carrier to a structural and regulatory architect in cellular physiology and prebiotic chemistry.

Autotomy is a unique phenotype whereby an animal sheds a body part to escape predation1-3. The timing and location of autotomy are tightly regulated by preformed planes of weakness (aka fracture planes) which facilitate tissue loss. While autotomy is often followed by regeneration, these phenotypes are rarely reported in mammals4-9. A notable exception are spiny mice (Acomys) which exhibit skin autotomy and more remarkably, complete tissue regeneration10-14. Presently, mechanisms underlying autotomy and complete regeneration in Acomys skin remain elusive. Here, we report the discovery of a honeycomb-like fracture lattice in Acomys skin whose design directs tissue destruction but also facilitates regenerative healing. Unlike the single continuous surface of a fracture plane, this fracture lattice consists of a three-dimensional array of hexagonal units whose boundaries guide tissue breakage. Moreover, we identify collagen VI as the main constituent of the fracture lattice and find that it is distinctly arranged to initiate fracturing and propagation of skin tearing. By preconditioning the tissue for autotomy, the fracture lattice dampens the damage-induced inflammatory response but also upregulates a pro-regenerative gene signature, accelerating skin appendage regeneration. Lastly, we discovered the key role of spiny hairs in fracture lattice formation, as inhibiting their development leads to abnormal pattern formation and changes in skin fracture mechanics. Our results present a novel example of a uniquely evolved structural adaptation in mammalian skin that links tissue patterning, autotomy and regeneration. We expect that the application of a modular compartment structure to artificial skin and other organ engineering may enhance resilience to injury and facilitate efficient regeneration.